Excel at Retail: Try It!

We are so confident that you will love Excel at Retail that we let you test drive it.

Follow the steps below to perform your analysis. With Excel at Retail you can go from 0 to 60 in less than 2 minutes.

Note: The models used on this page are some of the simplest in the Excel at Retail algorithm set. You can register for our Beta testing program to access more powerful models.



The data is a small random sample from the M5 retail forecasting competition dataset.

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Download the sample file for an example of the required file format.

Select the data from the drop down selector. The data will be displayed in the graph. Once you have selected the data you want, press the Analyze button. The analysis will take about 1 minute.



The total sales are summarized by month in the first table below. Once the analysis is performed the total detected lost sales (if any) are summarized by month in the second table.

You are ready to create a forecast.




The forecast by day is shown in the first graph below. The median forecast (there is a 50% chance demand will be lower and a 50% chance demand will be higher) as well as the p0.975 forecast (there is a 2.5% chance demand will be higher) and the p0.025 forecast (there is a 2.5% chance demand will be lower). The cumulative forecast (sum of the demand from the start of the forecasted period) is shown in the second graph. Note that the cumulative p0.975 forecast is not the sum of the daily p0.975 forecasts as strong demand days may be followed by less strong days. Excel at Retail computes the right probabilities for you.

Find the best order to place.

Single order



Excel at Retail computes the best order to place to achieve the desired service level.